Analyse et conception d'algorithmes et d'architectures embarqués à bord de satellites d'observation spatiale : application au satellite GAIA et généralisation à la compression d'images astronomiques
Bibliographic record
Abstract
The exploitation of the full benefits of chicken rearing by smallholder farmers in Sub-Saharan (SSA) Africa is often impeded by poultry diseases which is compounded by limited uptake of vaccination. We interrogate the structural and socioeconomic factors associated with vaccine uptake by women farmers in Southeastern Kenya. A mixed methods design with a convergent approach for comparison of quantitative and qualitative findings was adopted. This involved the administration of a cross section survey to 1274 households, conduct of 23 Focus Groups Discussions (FGDs) and 7 Key informant Interviews (KIIs). Chi Square and t-tests were used to identify factors associated with vaccine uptake. Logistics regression analysis was used to identify the influence of the structural and socioeconomic barriers to vaccine uptake. Findings indicate that having knowledge of Newcastle disease (ND) vaccine increases the likelihood of farmers vaccinating their chicken by up to 32.5 times (95% CI [8.46-124.53]) with a 1 unit increase in vaccine knowledge. A farmer's distance away from the nearest ND vaccine vendor was found to reduce the likelihood of farmers vaccinating their chicken by up to 4% (95% CI ([0.93-1.00]) for every 1-kilometre increase in distance away from the vaccine vendors. Farmers who considered vaccines to be effective in preventing ND were 39 times (95% CI [6.23-239.8]) more likely to use ND vaccines than those that did not consider ND vaccine to effective. We surmise that a comprehensive approach that addresses increased ND vaccine knowledge among smallholder women chicken farmers, proximity of ND vendors, as well as cost holds the potential for regular and increased ND vaccine uptake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".